ALL SOFTWARE EXERCISES
- EXERCISES HOME PAGE (813)
- Access 2010 (66)
- Access VBA Macros (17)
- Advanced VBA (29)
- Excel 2010 (83)
- Excel 2013 (10)
- Excel 2016 (0)
- Excel VBA Macros (37)
- Power BI - Excel 2013 (25)
- Power BI - Excel 2016 (23)
- Power BI Desktop (26)
- PowerPivot 2010 (26)
- Report Builder 3.0 (42)
- SQL (156)
- SSAS - multidimensional (21)
- SSAS - tabular (29)
- SSIS Integration Services (40)
- SSRS Reporting Services (53)
- Visual Basic (45)
- Visual C Sharp (65)
- WPF - Visual C# (20)
SSIS INTEGRATION SERVICES EXERCISES
Exercise: Export X Factor Series Data to SQL Server Table
This exercise is provided to allow potential course delegates to choose the correct Wise Owl Microsoft training course, and may not be reproduced in whole or in part in any format without the prior written consent of Wise Owl.
The answer to the exercise will be included and explained if you attend the relevant Wise Owl course (sadly, only in the UK for now).
You need a minimum screen resolution of about 700 pixels width to see our exercises. This is because they contain diagrams and tables which would not be viewable easily on a mobile phone or small laptop. Please use a larger tablet, notebook or desktop computer, or change your screen resolution settings.
In SQL Server Management Studio, open and run the script called Create table for series.sql in the above folder:
You should now have a skeleton table of series, ready to be filled in with data.
Create a new package called Serious series, and within this create two control flow tasks:
The first task should execute the SQL statement TRUNCATE TABLE tblSeries for the X Factor OLEDB connection, while the second one should be a data flow task which we'll configure in a moment. Ignore the yellow triangle!
Now configure the data flow task so that it:
- Takes data from the Excel workbook in the above folder (you'll need to create an Excel connection manager for this); and
- Exports it to the tblSeries table in the X_Factor database (using the existing OLEDB connection).
Run your package twice. You should get the following table of data:
Each time you run the package you get rid of old data in the table before adding new rows.
Close this package down.